code: def test_from_arrays_with_test_data(self):
      texts_train = np.array([f"train data {i}" for i in range(10)])
      labels_train = random_labels(10, 3, multi_label=True)
  
      text_field = get_text_field()
  
      dataset = PytorchTextClassificationDataset.from_arrays(
          texts_train, labels_train, text_field
      )
      self.assertTrue(dataset.is_multi_label)
  
      texts_test = np.array([f"test data {i}" for i in range(10)])
      labels_test = random_labels(10, 3, multi_label=True)
  
      dataset = PytorchTextClassificationDataset.from_arrays(
          texts_test, labels_test, text_field, train=False
      )
      self.assertEqual(10, len(dataset))
      self.assertTrue(dataset.is_multi_label)
      self.assertFalse("test" in dataset.vocab.stoi)
      self.assertTrue("data" in dataset.vocab.stoi)
  
file_path: small-text/tests/unit/small_text/integrations/pytorch/test_dataset_construction.py
imports: import unittest
  import pytest
  import numpy
  from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
  from tests.utils.datasets import random_labeling, random_labels
label_desc: Use image node_id 3 for calling the PytorchTextClassificationDatasetMultiLabelTest obj's underlying member method code with example usage: obj.test_from_arrays_with_test_data() without return types